Paper Details: Downloads: 2296
Serial Number: P1151653533
Title: Face Recognition based on Hidden Markov Model and Canny Operators
Authors: sameh magdy and Mohamed Ibrahim and tarek mahmoud
Abstract: In this paper, a new face recognition technique based on Hidden Markov Model (HMM), Pre-processing, and feature extraction (Canny) is proposed. Two main contributions are presented. In the pre-processing, the input image’s edge is fixed to five pixels and spacing between various parts of the pixels is fixed to a trial threshold. The second contribution is a new technique to extract the image's features by splitting the image into non-uniform height depending on the distribution of the foreground pixels. The foreground pixels are extracting by using the vertical sliding windows. The pre-processing steps have enhanced the performance of the system, for example, speed is the essence. In this paper, Hidden Markov models alongside the canny operator which proved high accuracy recognition of the face and its boundary. The presented technique is faster than some other techniques that are investigated for comparison. In addition to that, it reveals, its ability to recognize the normal face and face boundary very efficiently
Keywords: HMM, Canny Operator, Face Recognition, Accuracy
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume: 17
Issue: 1
Submission Date: 12/28/2016 12:00:00 AM
Review Date: 1/12/2017 12:00:00 AM
Publishing Date: 1/22/2017 3:02:44 AM
Article Downloads: 2296
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